[CI] Add elementwise and gemv examples to CI. (#458)

* [CI] Add elementwise and gemv examples to CI.

* fix lint

* test

* fix gemv lint

* fix lint

Author: Cunxiao2002

examples/elementwise/elementwise_add.py renamed to examples/elementwise/example_elementwise_add.py

@@ -1,3 +1,5 @@
+# Copyright (c) Tile-AI Corporation.
+# Licensed under the MIT License.
 import argparse
 import itertools
 import torch
@@ -13,7 +15,7 @@ def ref_program(x, y):
 def elementwise_add(M, N, block_M, block_N, in_dtype, out_dtype, threads):
 
     @T.prim_func
-    def main(A: T.Tensor((M, N), in_dtype), B: T.Tensor((M, N), in_dtype), C: T.Tensor((M, N),
+    def elem_add(A: T.Tensor((M, N), in_dtype), B: T.Tensor((M, N), in_dtype), C: T.Tensor((M, N),
                                                                                        out_dtype)):
         with T.Kernel(T.ceildiv(N, block_N), T.ceildiv(M, block_M), threads=threads) as (bx, by):
             start_x = bx * block_N
@@ -23,7 +25,7 @@ def main(A: T.Tensor((M, N), in_dtype), B: T.Tensor((M, N), in_dtype), C: T.Tens
                 x = start_x + local_x
                 C[y, x] = A[y, x] + B[y, x]
 
-    return main
+    return elem_add
 
 
 def get_configs(M, N):
@@ -49,13 +51,12 @@ def kernel(block_M=None, block_N=None, threads=None):
         )
     return autotuner.run(warmup=3, rep=20)
 
-
-if __name__ == "__main__":
+def main():
     parser = argparse.ArgumentParser()
     parser.add_argument("--m", type=int, default=512)
     parser.add_argument("--n", type=int, default=1024)
     parser.add_argument("--use_autotune", action="store_true", default=False)
-    args = parser.parse_args()
+    args, _ = parser.parse_known_args()
     M, N = args.m, args.n
 
     a = torch.randn(M, N, dtype=torch.float32, device="cuda")
@@ -72,3 +73,7 @@ def kernel(block_M=None, block_N=None, threads=None):
 
     out = kernel(a, b)
     torch.testing.assert_close(out, ref_program(a, b), rtol=1e-2, atol=1e-2)
+
+
+if __name__ == "__main__":
+    main()

examples/elementwise/test_example_elementwise.py

@@ -0,0 +1,12 @@
+# Copyright (c) Tile-AI Corporation.
+# Licensed under the MIT License.
+import tilelang.testing
+import example_elementwise_add
+
+
+def test_example_elementwise_add():
+    example_elementwise_add.main()
+
+
+if __name__ == "__main__":
+    tilelang.testing.main()

examples/gemv/example_gemv.py

@@ -304,11 +304,11 @@ def check_correctness_and_bench(kernel, N, K, bench_ref=True):
     print(f"TileLang Latency: {latency} ms\n")
 
 
-if __name__ == "__main__":
+def main():
     parser = argparse.ArgumentParser(description="GEMV Example")
     parser.add_argument("--n", type=int, default=1024, help="Matrix dimension N")
     parser.add_argument("--k", type=int, default=1024, help="Matrix dimension K")
-    args = parser.parse_args()
+    args, _ = parser.parse_known_args()
     N, K = args.n, args.k
     check_correctness_and_bench(naive_gemv(N, K, 128, 128), N, K)
     check_correctness_and_bench(naive_splitk_gemv(N, K, 32, 32), N, K)
@@ -318,13 +318,15 @@ def check_correctness_and_bench(kernel, N, K, bench_ref=True):
     print("Test passed!")
 
     best_result = get_best_config(N, K)
-    best_latency = best_result.latency
     best_config = best_result.config
-    ref_latency = best_result.ref_latency
     kernel = splitk_gemv_vectorized_tvm(N, K, *best_config)
     kernel = tl.compile(kernel, out_idx=-1)
     profiler = kernel.get_profiler()
     latency = profiler.do_bench(lambda x, y: x @ y.T, warmup=500)
     print(f"Torch Latency: {latency} ms")
     latency = profiler.do_bench(kernel, warmup=500)
     print(f"TileLang Latency: {latency} ms\n")
+
+
+if __name__ == "__main__":
+    main()

examples/gemv/test_example_gemv.py

@@ -0,0 +1,13 @@
+# Copyright (c) Tile-AI Corporation.
+# Licensed under the MIT License.
+import tilelang.testing
+
+import example_gemv
+
+
+def test_example_gemv():
+    example_gemv.main()
+
+
+if __name__ == "__main__":
+    tilelang.testing.main()